I'm a PhD candidate at Stanford and the Arc Institute working on machine learning for biomolecular design. I came to research from a pre-med path because I wanted to build tools that reach more people than I could treat one at a time, and I've become obsessed with the problem of developing machine learning models which can design medicines we otherwise couldn't find traditionally. I'm excited about companies at the intersection of AI and drug discovery that are overcoming challenges to collect valuable data that can be used to inform hypotheses, discover targets, design drugs, and iteratively improve hits across biological problems and modalities.

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What is a healthcare advancement you hope to see in your lifetime?

Moving beyond drugs which bind, inhibit or activate protein targets towards discovery of therapeutic enzymes which can fulfill functions potentially new-to-biology that work in humans.

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What excites you most about working with ARTIS?

Through helping evaluate and assess early-stage companies, I'm excited to learn about cutting edge technologies in TechBio and understand what it takes to commercialize them.

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What is the most influential content you read last year?

The Drug Hunters: The Improbable Quest to Discover New Medicines

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From your perspective, what recent innovation has had the greatest impact in tech/health?

The discovery of GLP1R agonists: these molecules proved one metabolic drug can modify outcomes across a dozen ostensibly unrelated diseases. In addition to renewing interest in BioPharma from an investment standpoint, they have shifted our understanding of therapeutics from things that can cure discrete conditions towards tools to improve and extend our quality of life, renewing interest in metabolism, aging and neurodegenerative disease

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What is your greatest accomplishment?

Using machine learning pipelines I've developed on tough biological problems (vaccine stabilization, antibody binder design) and demonstrating they can solve them in the wet-lab.

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